1. Field
The following description relates to a method of recognizing stairs in a three-dimensional (3D) data image wherein data points corresponding to stairs are detected in a 3D data image of a space in which stairs are located.
2. Description of the Related Art
To go up stairs, a humanoid or mobile robot may need to recognize the position of the stairs with reference to the location of the robot, riser heights, or tread depths of the stairs, for example. To accomplish this, the robot may be provided with a 3D sensor to acquire a 3D data image of a space in which the stairs are located. The robot may recognize the stairs by processing and analyzing the 3D data image through a microcontroller provided in the robot.
In an Iterative Closest Point (ICP) method, which is a conventional stair recognition method, a 3D model detected from a 3D data image and a stored 3D model are matched and compared. Specifically, in the ICP method, the two 3D models are matched through repetitive calculation such that the distance between the two 3D models is minimized. Accordingly, the ICP method requires stored 3D models and also requires repetitive calculation for matching between the detected 3D model and the stored 3D models. In another conventional stair recognition method, lines are detected through vertices in the 3D data image and stairs are recognized based on the detected lines. This method recognizes treads of stairs assuming that two consecutive lines, which belong to stairs in a 3D data image, are located in the same plane. Such a method of detecting lines in a 3D data image has low stair recognition accuracy because the method is sensitive to errors due to characteristics of 3D data images.